Databricks Certified Data Engineer Professional

Exam format

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Databricks Certified Data Engineer Professional Exam Format

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Everything the official exam blueprint specifies: question count, time limit, scoring and the weight each domain carries. The Databricks Certified Data Engineer Professional (DE Pro) exam validates advanced skills in designing, building, and optimizing production-grade data pipelines on the Databricks Lakehouse Platform. It covers Delta Lake, Structured Streaming, Unity Catalog, performance tuning, security, and governance. Candidates must demonstrate proficiency in Python, , Spark, and real-world data engineering scenarios.

59 questions
120 min
70% to pass
10 domains

Exam facts at a glance

The published specifications for this certification.

SpecificationValue
Questions59
Time limit120 minutes (122s per question)
Passing score70% — Not published by the provider
Domains10
LevelProfessional
Question bank here59 questions
Published format59 scored multiple-choice questions plus up to 10 unscored questions (current exam through Oct 8, 2026); 120 minutes. From Oct 9, 2026 the exam moves to 60 scored questions.
SourceOfficial exam specification, published by the vendor

Official domain weights

The percentage of the exam each domain carries. Weight your revision by these numbers, not by what you find hardest.

DomainWeightTopicsPractice Qs
Data Modelling6%
  • Designing star and snowflake schemas on Databricks
  • Implementing slowly changing dimensions (Type 1, 2, 3) in Delta Lake
  • Using dimensional modeling best practices for analytical workloads
  • +2 more
3
Data Governance7%
  • Setting up Unity Catalog metastore, zones, and permissions
  • Managing data ownership and governance policies
  • Cataloging assets with tags, documentation, and search
  • +2 more
4
Monitoring and Alerting10%
  • Monitoring jobs and pipelines using Databricks Jobs UI and APIs
  • Setting up alerts in Databricks dashboards
  • Using Spark UI, Ganglia metrics, and cluster event logs
  • +3 more
6
Debugging and Deploying10%
  • Debugging Spark jobs using UI, logs, and metrics
  • Handling common errors (OutOfMemory, shuffle failures, serialization)
  • Testing data pipelines with Databricks notebooks and unit testing
  • +2 more
6
Data Sharing and Federation5%
  • Setting up Delta Sharing for secure data collaboration
  • Configuring read-only and write shares
  • Creating recipient tokens and managing shared tables
  • +2 more
3
Data Ingestion & Acquisition7%
  • Configuring auto-loader for incremental ingestion from cloud storage
  • Ingesting data from various sources (files, Kafka, JDBC, APIs)
  • Handling schema inference and schema evolution during ingestion
  • +2 more
4
Cost & Performance Optimisation13%
  • Optimizing Spark configuration (shuffle partitions, executor sizing)
  • Using Auto-Scaling and spot instances for cost savings
  • Partitioning, bucketing, and Z-ordering for performance
  • +5 more
8
Ensuring Data Security and Compliance10%
  • Implementing row-level and column-level security with Unity Catalog
  • Using data masking and dynamic views for PII protection
  • Managing access control lists (ACLs) and service principals
  • +3 more
6
Data Transformation, Cleansing, and Quality10%
  • Implementing data quality checks with Delta Live Tables EXPECTATIONS
  • Using Great Expectations integration for validation
  • Cleansing data with null handling, deduplication, and type casting
  • +2 more
6
Developing Code for Data Processing using Python and22%
  • Writing efficient PySpark and Spark transformations
  • Using DataFrames and Datasets APIs in Python
  • Applying window functions, aggregations, and joins
  • +6 more
13

The heaviest domain is Data Modelling at 6%, and that is where lost points cost you the most. Certilum scores you per domain so you can see the difference between a knowledge gap and a formatting problem.

Note from the vendor record: The official exam guide PDF (dated October 2026) presents two columns: the current exam with 59 scored questions through Oct 8, 2026 and a new exam with 60 scored questions from Oct 9, 2026; time limit, fee, delivery and prerequisites are identical for both. Neither the certification page nor the official exam guide states a passing score or percentage, so the passing score is recorded as not published. Certification is valid for 2 years and recertification requires taking the current live exam; no prerequisite is required but related training and about one year of hands-on data engineering experience are recommended. Unscored items may be included and do not affect the score. Official exam page

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